Wednesday, May 1, 2013

A How-to Guide: Starting the “Big Data” Conversation

By Evan Robertson, Project Associate.

Last week, Atlanta hosted its first ever Big Data Week. During the week’s festivities, cities across the globe celebrate and contemplate big data’s social, political, technological, and commercial implications. As a diverse group of entrepreneurs, professors, and business leaders gave their big data insights, I kept facing the question: What role do local governments and chambers of commerce play in the “Big Data” discussion? But I am getting ahead of myself, first a little background.

Over the course of a normal day, the average human generates voluminous amounts of information. Thatinstagramed picture of your cute kitten? Well, that is saved on a server somewhere in the world. Once everyone wants to save multiple pictures of their cat...it starts to add up. A 2010 McKinsey and Company study found that consumers in that year would generate six exabytes of data. For those not familiar with an exabyte (I admittedly wasn’t either), six exabytes equals 6,442,450,944 gigabytes. If you wanted to store that amount of data on a 500GB hard drive, you’d need 12,884,902 of them. To top it all off, companies are finding new ways of collecting consumer information every day.

Progressive Insurance rolled out its “Snapshot” program in 2010. Drivers who sign-up for the program allow Progressive to install a data recorder in their car which records basic telemetry information (braking, acceleration habits) as well as what time of day they drive and for how long. As a consumer, if your driving habits fall within the threshold of what progressive deems “safe,” you get a discount. In exchange, Progressive gets a massive amount of information on its consumers’ habits which can give them an edge over their competition. Think about it, insurance companies make money by not paying claims. If Progressive deduces from their data that people who slam on their brakes, drive an average of 22 miles per day, and drive between 12:00am and 4:00am once a week are the least accident prone, then the company can build a strategy on recruiting these drivers or changing driving habits of their existing customer base. Fewer claims equal more money.

Progressive isn’t the only one collecting data to gain greater insight into consumer preferences. Cox Communications is in the process of rolling out cable boxes that record customer remote control clicks. Their long-term vision is to supplant Nielsen (the company that produces the TV ratings) with their own internal system which can better inform advertisers to which demographics are watching which shows and at what times. By collecting this data, Cox Communications gains insight into their customers’ habits. Once again, this data adds value to business operations and provides a level of insight not easily matched by their competitors. That is the major selling point of big data: it grants insight over your competitors, a competitive edge if you will.

Big data is essentially the combination of many types of data which are then analyzed using statistical and mathematical algorithms. In Progressive’s case, big data would not only entail their drivers’ data but would also involve merging that data they gather with other information. For instance, combining driving habits with the drivers’ payment history and Google Search history is what big data is all about. By combining these data, Progressive could potentially figure out that people who slam on their brakes, make their payments on time, and search for the term “I brake for squirrels” might be less accident prone than someone who slams on their brakes, pays on time, but searches for “symptoms of road rage.” Big data is the merger of the voluminous data you put out (tweets, updates, grocery store purchases, etc.) into a common format that a company can analyze to deduce insights.

So, what role do local governments and chambers of commerce (LGCC) have to play?

First, a caveat. In the big data discussion, it is critical for tech-savvy entrepreneurs, Chief Information Officers, and other business community members to lead the discussion. You can think of the big data entrepreneurs and business owners as an independent community that needs to be internally self-sustaining and driven by the private sector. An outside voice attempting to guide the process may adversely impact the community’s ability to rapidly adapt to change, a critical factor in the success of communities centered on emerging technologies. We all want to be leaders, but in this case LGCCs have more important roles: connecting and convening.

One observation from Big Data Week Atlanta 2013: there exists a disconnect between business leaders (C-level executives), their technology workers, and big data entrepreneurs. Simply put, C-level executives are wary of “big data” because they’ve already spent millions upon millions of dollars building business intelligence datacenters that didn’t meet their expected return on investment. Now their IT workers are pushing them to purchase more equipment and software required for big data storage and analysis. Executives are rightly skeptical about shelling out more money on cutting-edge technology, especially because big data’s insights aren’t readily apparent to leadership and it’s hard to separate valuable insights from the mundane. Executives need a proof of concept. They need to see big data in action in order to fully piece together 1) what big data is and 2) how it will give their company an edge over others.

A few potential strategies developed by audience members during a Power in Numbers: Growing Atlanta’s Data Science Talent breakout session led by Hans Utz (Deputy Chief Operating Officer at the City of Atlanta) touch on talent development, connecting talent with the broader business community, and getting the conversation started:

1) Hold a technology showcase at a local event space: Allow technology entrepreneurs (assuming they’ve already protected their intellectual property) to demonstrate their products to local business leaders.

2) Create a big data technology challenge: This entails asking a large company to identify a particular challenge they feel big data could solve, and offering a cash prize (internship, job offer, scholarship, venture capital, etc.) to the team that solves it first. This could take the form of a week or day long hackathon.

3) Create big data entrepreneurial zones: Zones would essentially be co-working spaces at local companies, or public-sector facilities that would allow big data entrepreneurs access to subsidized, collaborative space. Zones should be open to everyone interested in big data and promote interdisciplinary interaction wherever possible.

4) Give entrepreneurs access to public data: Cities generate massive amounts of data, and are a treasure trove for entrepreneurs interested in big data. Govathon hosted by the City of Atlanta and Start-up Atlanta is an excellent example of getting entrepreneurs excited about and used to working with big data.

In the 2010 Big Data study, McKinsey and Company estimated that there will soon be a big data talent shortage between 140,000 to 190,000 technology workers who collect, store, and analyze big data with an additional 1,500,000 managers and analysts who will need to be well versed in big data and who can leverage its findings effectively. LGCCs play a crucial role in ensuring that your local community can supply the workers that big data demands. Local governments and Chambers must work hand in hand with the business leaders and higher education institutions to ensure that the community is turning out workers with a broad, but deep, set of skills including computer programing, mathematics, statistics, design, and visualization.

A few lessons from Big Data Week:

1) Before developing new big data talent, focus on what you already have: Those C-level executives who spent countless millions on business intelligence infrastructure and hiring workers to support that infrastructure? Well, they’d probably like to be able to repurpose those investments to meet their big data needs. Worker retraining (given the complexity of educating individuals in the broad set of skills demanded by big data) is the most expedient way to meet the talent shortage.

2) Create “data” labs for young entrepreneurs at mid- and large-size businesses: As pointed out by Seth Ryan during “What’s the Big Opportunity of Big Data?” discussion, young big data talent graduating from local universities are increasingly attracted to tech start-ups. This leaves a dearth of talent for mid-size businesses (who are still hesitant to invest in big data) and large-size firms (who can invest in the infrastructure but don’t have the talent to run it). One way to attract young talent to these types of business is to give them a “start-up” feel. Data labs would allow big data entrepreneurs to access and more easily experiment with large data sets.

3) Foster a culture of big data collaboration: Big data requires skill sets from a variety of fields. Fostering relationships across knowledge sectors will help to expand the local workforce’s capability. This culture of collaboration could begin at local universities, focusing on forging relationships between design, computer science, mathematics, management, and public policy departments. Of course, you should also focus on forging interdisciplinary teams throughout the local private and public sectors.

Admittedly, big data is another ambiguous term that has popped up in the job creation debate. So, let me kill the hype: big data probably won’t serve the basis of another industrial revolution that will ensure America’s future prosperity for generations to come. However, in an increasingly competitive marketplace, it will allow companies to better leverage their information and consumer knowledge giving themselves an edge in the rapidly evolving global marketplace.